import gradio as gr
from transformers import pipeline, MarianMTModel, AutoTokenizer
import os
import azure.cognitiveservices.speech as speechsdk
import matplotlib.pyplot as plt
import numpy as np

dialects = {"Palestinian/Jordanian": "P", "Syrian": "S", "Lebanese": "L", "Egyptian": "E"}

# translator_en2ar = pipeline(task="translation", model="guymorlan/English2Dialect")
translator_en2ar = MarianMTModel.from_pretrained("guymorlan/English2Dialect", output_attentions=True)
tokenizer_en2ar = AutoTokenizer.from_pretrained("guymorlan/English2Dialect")
translator_ar2en = MarianMTModel.from_pretrained("guymorlan/Shami2English", output_attentions=True)
tokenizer_ar2en = AutoTokenizer.from_pretrained("guymorlan/Shami2English")
transliterator = pipeline(task="translation", model="guymorlan/DialectTransliterator")

speech_config = speechsdk.SpeechConfig(subscription=os.environ.get('SPEECH_KEY'), region=os.environ.get('SPEECH_REGION'))

def generate_diverging_colors(num_colors, palette='Set3'): # courtesy of ChatGPT
    # Generate a colormap with a specified number of colors
    cmap = plt.cm.get_cmap(palette, num_colors)

    # Get the RGB values of the colors in the colormap
    colors_rgb = cmap(np.arange(num_colors))

    # Convert the RGB values to hexadecimal color codes
    colors_hex = [format(int(color[0]*255)<<16|int(color[1]*255)<<8|int(color[2]*255), '06x') for color in colors_rgb]

    return colors_hex


def align_words(outputs, tokenizer, encoder_input_ids, decoder_input_ids, threshold=0.4, skip_first_src=True):
    alignment = []
    for i, tok in enumerate(outputs.cross_attentions[2][0][7]):
        alignment.append([[i], (tok > threshold).nonzero().squeeze(-1).tolist()])

    merged = []
    for i in alignment:
        token = tokenizer.convert_ids_to_tokens([decoder_input_ids[0][i[0]]])[0]
        if token not in tokenizer.convert_tokens_to_ids(["</s>", "<pad>", "<unk>"]):
            if merged:
                tomerge = False
                # check overlap with previous entry
                for x in i[1]:
                    if x in merged[-1][1]:# or tokenizer.convert_ids_to_tokens([encoder_input_ids[0][x]])[0][0] != "▁": 
                        tomerge = True
                        break
                # if first character is not a "▁"
                if  token[0] != "▁":
                    tomerge = True
                if tomerge:
                    merged[-1][0] += i[0]
                    merged[-1][1] += i[1]
                else:
                    merged.append(i)
            else:
                merged.append(i)

    colordict = {}
    ncolors = 0
    for i in merged:
        src_tok = [f"src_{x}" for x in i[0]]
        trg_tok = [f"trg_{x}" for x in i[1]]
        all_tok = src_tok + trg_tok
        # see if any tokens in entry already have associated color
        newcolor = None
        for t in all_tok:
            if t in colordict:
                newcolor = colordict[t]
                break
        if not newcolor:
            newcolor = ncolors
            ncolors += 1
        for t in all_tok:
            if t not in colordict:
                colordict[t] = newcolor

    colors = generate_diverging_colors(ncolors, palette="Set2")
    id_to_color = {i: c for i, c in enumerate(colors)}
    for k, v in colordict.items():
        colordict[k] = id_to_color[v]


    tgthtml = []
    for i, token in enumerate(decoder_input_ids[0]):
        if f"src_{i}" in colordict:
            label = f"src_{i}"
            tgthtml.append(f"<span style='color: #{colordict[label]}'>{tokenizer.convert_ids_to_tokens([token])[0]}</span>")
        else:
            tgthtml.append(f"<span style='color: --color-text-body'>{tokenizer.convert_ids_to_tokens([token])[0]}</span>")
    tgthtml = "".join(tgthtml)
    tgthtml = tgthtml.replace("▁", " ")
    tgthtml = f"<span style='font-size: 30px'>{tgthtml}</span>"

    srchtml = []
    for i, token in enumerate(encoder_input_ids[0]):
        if skip_first_src and i == 0:
            continue
        if f"trg_{i}" in colordict:
            label = f"trg_{i}"
            srchtml.append(f"<span style='color: #{colordict[label]}'>{tokenizer.convert_ids_to_tokens([token])[0]}</span>")
        else:
            srchtml.append(f"<span style='color: --color-text-body'>{tokenizer.convert_ids_to_tokens([token])[0]}</span>")
    srchtml = "".join(srchtml)
    srchtml = srchtml.replace("▁", " ")
    srchtml = f"<span style='font-size: 30px'>{srchtml}</span>"
    return srchtml, tgthtml

def translate_english(input_text, include):
    if not input_text:
        return "", "", "", "", ""

    inputs = [f"{val} {input_text}" for val in dialects.values()]

    sy, lb, eg = "SYR" in include, "LEB" in include, "EGY" in include
    # remove 2nd element if sy is false
    if not eg:
        inputs.pop()
    if not lb:
        inputs.pop()
    if not sy:
        inputs.pop()

    input_tokens = tokenizer_en2ar(inputs, return_tensors="pt").input_ids
    # print(input_tokens)
    outputs =  translator_en2ar.generate(input_tokens)
    # print(outputs)

    encoder_input_ids = input_tokens[0].unsqueeze(0)
    decoder_input_ids = outputs[0].unsqueeze(0)


    decoded = tokenizer_en2ar.batch_decode(outputs, skip_special_tokens=True)
    # print(decoded)
    pal_out = decoded[0]
    sy_out = decoded[1] if sy else ""
    lb_out = decoded[1 + sy] if lb else ""
    eg_out = decoded[1 + sy + lb] if eg else ""

    if "Colorize" in include:
        html_outputs = translator_en2ar(input_ids=encoder_input_ids, decoder_input_ids=decoder_input_ids)

        # set dynamic threshold
        # print(input_tokens, input_tokens.shape)
        if input_tokens.shape[1] < 10:
            threshold = 0.4
        elif input_tokens.shape[1] < 20:
            threshold = 0.10
        else:
            threshold = 0.05

        print("threshold", threshold)

        srchtml, tgthtml = align_words(html_outputs, tokenizer_en2ar, encoder_input_ids, decoder_input_ids, threshold)
        palhtml = f"{srchtml}<br><br><div style='direction: rtl'>{tgthtml}</div>"
    else:
        palhtml = f"<div style='font-size: 30px; direction: rtl'>{pal_out}</div>"


    return palhtml, pal_out, sy_out, lb_out, eg_out

def translate_arabic(input_text, include=["Colorize"]):
    if not input_text:
        return ""

    input_tokens = tokenizer_ar2en(input_text, return_tensors="pt").input_ids
    # print(input_tokens)
    outputs =  translator_ar2en.generate(input_tokens)
    # print(outputs)

    encoder_input_ids = input_tokens[0].unsqueeze(0)
    decoder_input_ids = outputs[0].unsqueeze(0)

    decoded = tokenizer_en2ar.batch_decode(outputs, skip_special_tokens=True)
    # print(decoded)

    print(include)
    if "Colorize" in include:
        html_outputs = translator_ar2en(input_ids=encoder_input_ids, decoder_input_ids=decoder_input_ids)

        # set dynamic threshold
        # print(input_tokens, input_tokens.shape)
        if input_tokens.shape[1] < 20:
            threshold = 0.1
        elif input_tokens.shape[1] < 30:
            threshold = 0.01
        else:
            threshold = 0.05

        print("threshold", threshold)

        srchtml, tgthtml = align_words(html_outputs, tokenizer_ar2en, encoder_input_ids, decoder_input_ids, threshold, skip_first_src=False)
        enhtml = f"<div style='direction: rtl'>{srchtml}</div><br><br><div>{tgthtml}</div>"
    else:
        enhtml = f"<div style='font-size: 30px;'>{decoded[0]}</div>"

    return enhtml

def get_audio(input_text):
    audio_config = speechsdk.audio.AudioOutputConfig(filename=f"{input_text}.wav")
    speech_config.speech_synthesis_voice_name='ar-SY-AmanyNeural'
    speech_synthesizer = speechsdk.SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
    speech_synthesis_result = speech_synthesizer.speak_text_async(input_text).get()
    return f"{input_text}.wav"

def get_transliteration(input_text, include=["Translit."]):
    if "Translit." not in include:
        return ""
    result = transliterator([input_text])
    return result[0]["translation_text"]


bla = """
"""
css = """
#liter textarea, #trans textarea { font-size: 25px;}
#trans textarea { direction: rtl; }
#check { border-style: none !important; }
:root {--button-secondary-background-focus: #2563eb !important;
       --button-secondary-background-base: #2563eb !important;
       --button-secondary-background-hover: linear-gradient(to bottom right, #0692e8, #5859c2);
       --button-secondary-text-color-base: white !important;
       --button-secondary-text-color-hover: white !important;
       --button-secondary-background-focus: rgb(51 122 216 / 70%) !important;
       --button-secondary-text-color-focus: white !important}
.dark {--button-secondary-background-base: #2563eb !important;
       --button-secondary-background-focus: rgb(51 122 216 / 70%) !important;
       --button-secondary-background-hover: linear-gradient(to bottom right, #0692e8, #5859c2)}
.feather-music { stroke: #2563eb; }
"""

def toggle_visibility(include):
    outs = [gr.Textbox.update(visible=True)] * 4
    if "Translit." not in include:
        outs[0] = gr.Textbox.update(visible=False)
    if "SYR" not in include:
        outs[1] = gr.Textbox.update(visible=False)
    if "LEB" not in include:
        outs[2] = gr.Textbox.update(visible=False)
    if "EGY" not in include:
        outs[3] = gr.Textbox.update(visible=False)

    return outs

with gr.Blocks(title = "Levantine Arabic Translator", css=css, theme="default") as demo:
    gr.HTML("<h2><span style='color: #2563eb'>Levantine Arabic</span> Translator</h2>")
    with gr.Tab('En > Ar'):
        with gr.Row():
            with gr.Column():
                input_text = gr.Textbox(label="Input", placeholder="Enter English text", lines=2)
                gr.Examples(["I wanted to go to the store yesterday, but it rained", "How are you feeling today?"], input_text)
                btn = gr.Button("Translate", label="Translate")
                with gr.Row():
                    include = gr.CheckboxGroup(["Translit.", "SYR", "LEB", "EGY", "Colorize"], 
                                               label="Disable features to speed up translation",
                                               value=["Translit.", "EGY", "Colorize"])
                gr.Markdown("Built by [Guy Mor-Lan](mailto:guy.mor@mail.huji.ac.il). Pronunciation model is specifically tailored to urban Palestinian Arabic. Text-to-speech uses Microsoft Azure's API and may provide different result from the transliterated pronunciation.")

            with gr.Column():
                with gr.Box(label = "Palestinian"):
                    gr.Markdown("Palestinian")
                    with gr.Box():
                        pal_html = gr.HTML("<br>", visible=True, label="Palestinian", elem_id="main")
                pal = gr.Textbox(lines=1, label="Palestinian", elem_id="trans", visible=False)
                pal_translit = gr.Textbox(lines=1, label="Palestinian Pronunciation (Urban)", elem_id="liter")
                sy = gr.Textbox(lines=1, label="Syrian", elem_id="trans", visible=False)
                lb = gr.Textbox(lines=1, label="Lebanese", elem_id="trans", visible=False)
                eg = gr.Textbox(lines=1, label="Egyptian", elem_id="trans")
                # with gr.Row():
                audio = gr.Audio(label="Audio - Palestinian", interactive=False)
                audio_button = gr.Button("Get Audio", label="Click Here to Get Audio")
                audio_button.click(get_audio, inputs=[pal], outputs=[audio])
        btn.click(translate_english,inputs=[input_text, include], outputs=[pal_html, pal, sy, lb, eg], api_name="en2ar", _js="function jump(x, y){document.getElementById('main').scrollIntoView(); return [x, y];}")
        input_text.submit(translate_english, inputs=[input_text, include], outputs=[pal_html, pal, sy, lb, eg],scroll_to_output=True)
        pal.change(get_transliteration, inputs=[pal, include], outputs=[pal_translit]);
        include.change(toggle_visibility, inputs=[include], outputs=[pal_translit, sy, lb, eg])

    with gr.Tab('Ar > En'):
        with gr.Row():
            with gr.Column():
                input_text = gr.Textbox(label="Input", placeholder="Enter Levantine Arabic text", lines=1, elem_id="trans")
                gr.Examples(["خلينا ندور على مطعم تاني", "قديش حق البندورة؟"], input_text)
                btn = gr.Button("Translate", label="Translate")
                gr.Markdown("Built by [Guy Mor-Lan](mailto:guy.mor@mail.huji.ac.il).")
            with gr.Column():
                with gr.Box(label = "English"):
                    gr.Markdown("English")
                    with gr.Box():
                        eng = gr.HTML("<br>", label="English", elem_id="main")
        btn.click(translate_arabic,inputs=input_text, outputs=[eng], api_name = "ar2en")

    with gr.Tab("Transliterate"):
        with gr.Row():
            with gr.Column():
                input_text = gr.Textbox(label="Input", placeholder="Enter Levantine Arabic text", lines=1)
                gr.Examples(["خلينا ندور على مطعم تاني", "قديش حق البندورة؟"], input_text)
                btn = gr.Button("Transliterate", label="Transliterate")
                gr.Markdown("Built by [Guy Mor-Lan](mailto:guy.mor@mail.huji.ac.il)")
            with gr.Column():
                translit = gr.Textbox(label="Transliteration", lines=1, elem_id="liter")
        btn.click(get_transliteration, inputs=input_text, outputs=[translit])


demo.launch()